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Articles

Probabilistic multi-objective optimum combined inspection and monitoring planning and decision making with updating

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Pages 1487-1505 | Received 08 Aug 2021, Accepted 16 Feb 2022, Published online: 27 Apr 2022

References

  • AASHTO. (2017). The manual for bridge evaluation (3rd ed.). American Association of State Highway and Transportation Officials (AASHTO).
  • Alencar, G., de Jesus, A., da Silva, J. G. S., & Calçada, R. (2019). Fatigue cracking of welded railway bridges: A review. Engineering Failure Analysis, 104, 154–176. doi:10.1016/j.engfailanal.2019.05.037
  • Ang, A. H.-S., & Tang, W. H. (2007). Probability concepts in engineering: Emphasis on applications to civil and environmental engineering (2nd ed.). Wiley.
  • Arora, J. S. (2017). Introduction to optimum design (4th ed.). Elsevier.
  • Biondini, F., & Frangopol, D. M. (2016). Life-cycle performance of deteriorating structural systems under uncertainty: Review. Journal of Structural Engineering, 142(9), 1–17. doi:10.1061/(ASCE)ST.1943-541X.0001544
  • Brownjohn, J. M. W. (2007). Structural health monitoring of civil infrastructure. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 365(1851), 589–622. doi:10.1098/rsta.2006.1925
  • Chang, P. C., Flatau, A., & Liu, S. C. (2003). Review paper: Health monitoring of civil infrastructure. Structural Health Monitoring, 2(3), 257–267. doi:10.1177/1475921703036169
  • Chen, N. Z., Wang, G., & Guedes Soares, C. (2011). Palmgren-Miner’s rule and fracture mechanics-based inspection planning. Engineering Fracture Mechanics, 78(18), 3166–3182. doi:10.1016/j.engfracmech.2011.08.002
  • Chiandussi, G., Codegone, M., Ferrero, S., & Varesio, F. E. (2012). Comparison of multi-objective optimization methodologies for engineering applications. Computers & Mathematics with Applications, 63(5), 912–942. doi:10.1016/j.camwa.2011.11.057
  • Connor, R. J., & Lloyd, J. B. (2017). Maintenance actions to address fatigue cracking in steel bridge structures: Proposed guidelines and commentary. Purdue University.
  • Das, S., Saha, P., & Patro, S. K. (2016). Vibration-based damage detection techniques used for health monitoring of structures: A review. Journal of Civil Structural Health Monitoring, 6(3), 477–507. doi:10.1007/s13349-016-0168-5
  • Deng, H., Yeh, C. H., & Willis, R. J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers & Operations Research, 27(10), 963–973. doi:10.1016/S0305-0548(99)00069-6
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22(7), 763–770. doi:10.1016/0305-0548(94)00059-H
  • Diamantidis, D., & Sykora, M. (2019). Implementing information gained through structural health monitoring-proposal for standards. Proceedings of the 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13), Seoul, South Korea May 26–30, 2019.
  • Dong, Y., & Frangopol, D. M. (2016). Incorporation of risk and updating in inspection of fatigue-sensitive details of ship structures. International Journal of Fatigue, 82(3), 676–688. doi:10.1016/j.ijfatigue.2015.09.026
  • Ellingwood, B. R., & Mori, Y. (1997). Reliability-based service life assessment of concrete structures in nuclear power plants: Optimum inspection and repair. Nuclear Engineering and Design, 175(3), 247–258. doi:10.1016/S0029-5493(97)00042-3
  • Elmasry, M., Zayed, T., & Hawari, A. (2019). Multi-objective optimization model for inspection scheduling of sewer pipelines. Journal of Construction Engineering and Management, 145(2), 04018129. doi:10.1061/(ASCE)CO.1943-7862.0001599
  • Enright, M. P., & Frangopol, D. M. (1999). Condition prediction of deteriorating concrete bridges using Bayesian updating. Journal of Structural Engineering, 125(10), 1118–1124. doi:10.1061/(ASCE)0733-9445(1999)125:10(1118)
  • FHWA. (2015). Bridge maintenance reference manual. Publication No. FHWA-NHI-14-050, Federal Highway Administration (FHWA).
  • Fisher, J. W. (1984). Fatigue and fracture in steel bridges. John Wiley & Sons.
  • Frangopol, D. M. (2011). Life-cycle performance, management, and optimization of structural systems under uncertainty: Accomplishments and challenges. Structure and Infrastructure Engineering, 7(6), 389–413. doi:10.1080/15732471003594427
  • Frangopol, D. M., & Kim, S. (2014). Chapter 10: Bridge health monitoring. In Bridge engineering handbook (2nd ed., Vol. 5, pp. 247–268, W.-F. Chen & L. Duan, Eds.). CRC Press/Taylor & Francis Group, Boca Raton.
  • Frangopol, D. M., & Kim, S. (2019). Life-cycle of structures under uncertainty: Emphasis on fatigue-sensitive civil and marine structures. CRC Press, A Science Publishers Book, Boca Raton, London, New York.
  • Frangopol, D.M., & Kim, S. (2022). Bridge Safety, Maintenance and Management in a Life-Cycle Context. CRC Press, A Science Publishers Book, Boca Raton, London, New York.
  • Frangopol, D. M., Lin, K. Y., & Estes, A. C. (1997). Life-cycle cost design of deteriorating structures. Journal of Structural Engineering, 123(10), 1390–1401. doi:10.1061/(ASCE)0733-9445(1997)123:10(1390)
  • Frangopol, D. M., & Soliman, M. (2016). Life-cycle of structural systems: Recent achievements and future directions. Structure and Infrastructure Engineering, 12(1), 1–20. doi:10.1080/15732479.2014.999794
  • Frangopol, D. M., Strauss, A., & Kim, S. (2008a). Bridge reliability assessment based on monitoring. Journal of Bridge Engineering, 13(3), 258–270. doi:10.1061/(ASCE)1084-0702(2008)13:3(258)
  • Frangopol, D. M., Strauss, A., & Kim, S. (2008b). Use of monitoring extreme data for the performance prediction of structures: General approach. Engineering Structures, 30(12), 3644–3653. doi:10.1016/j.engstruct.2008.06.010
  • Garbatov, Y., & Guedes Soares, C. (2001). Cost and reliability based strategies for fatigue maintenance planning of floating structures. Reliability Engineering & System Safety, 73(3), 293–301. doi:10.1016/S0951-8320(01)00059-X
  • Ge, B., & Kim, S. (2021). Determination of appropriate updating parameters for effective life-cycle management of deteriorating structures under uncertainty. Structure and Infrastructure Engineering, 17(9), 1284–1298. doi:10.1080/15732479.2020.1809466
  • Hasting, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1), 97–109. doi:10.2307/2334940
  • Heitner, B., Obrien, E. J., Yalamas, T., Schoefs, F., Leahy, C., & Decatoire, R. (2019). Updating probabilities of bridge reinforcement corrosion using health monitoring data. Engineering Structures, 190, 41–51. doi:10.1016/j.engstruct.2019.03.103
  • Huang, T. L., Zhou, H., Chen, H. P., & Ren, W. X. (2016). Stochastic modelling and optimum inspection and maintenance strategy for fatigue affected steel bridge members. Smart Structures and Systems, 18(3), 569–584. doi:10.12989/sss.2016.18.3.569
  • Hwang, C. L., Lai, Y. J., & Liu, T. Y. (1993). A new approach for multiple objective decision making. Computers & Operations Research, 20(8), 889–899. doi:10.1016/0305-0548(93)90109-V
  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making-methods and applications, a state-of-the-art survey. Springer-Verlag.
  • Kailath, T. (1967). The divergence and Bhattacharyya distance measures in signal selection. IEEE Transactions on Communications, 15(1), 52–60. doi:10.1109/TCOM.1967.1089532
  • Kim, S., & Frangopol, D. M. (2011a). Inspection and monitoring planning for RC structures based on minimization of expected damage detection delay. Probabilistic Engineering Mechanics, 26(2), 308–320. doi:10.1016/j.probengmech.2010.08.009
  • Kim, S., & Frangopol, D. M. (2011b). Optimum inspection planning for minimizing fatigue damage detection delay of ship hull structures. International Journal of Fatigue, 33(3), 448–459. doi:10.1016/j.ijfatigue.2010.09.018
  • Kim, S., & Frangopol, D. M. (2011c). Cost-based optimum scheduling of inspection and monitoring for fatigue-sensitive structures under uncertainty. Journal of Structural Engineering, 137(11), 1319–1331. doi:10.1061/(ASCE)ST.1943-541X.0000365
  • Kim, S., & Frangopol, D. M. (2011d). Probabilistic bicriterion optimum inspection/monitoring planning: Applications to naval ships and bridges under fatigue. Structure and Infrastructure Engineering, 8(10), 1–927. doi:10.1080/15732479.2011.574811
  • Kim, S., & Frangopol, D. M. (2018a). Decision making for probabilistic fatigue inspection planning based on multi-objective optimization. International Journal of Fatigue, 111, 356–368. doi:10.1016/j.ijfatigue.2018.01.027
  • Kim, S., & Frangopol, D. M. (2018b). Multi-objective probabilistic optimum monitoring planning considering fatigue damage detection, maintenance, reliability, service life and cost. Structural and Multidisciplinary Optimization, 57(1), 39–54. doi:10.1007/s00158-017-1849-3
  • Kim, S., & Frangopol, D. M. (2020). Computational platform for probabilistic optimum monitoring planning for effective and efficient service life management. Journal of Civil Structural Health Monitoring, 10(1), 1–15. doi:10.1007/s13349-019-00365-4
  • Kim, S., Frangopol, D. M., & Soliman, M. (2013). Generalized probabilistic framework for optimum inspection and maintenance planning. Journal of Structural Engineering, 139(3), 435–447. doi:10.1061/(ASCE)ST.1943-541X.0000676
  • Kim, S., Frangopol, D. M., & Zhu, B. (2011). Probabilistic optimum inspection/repair planning to extend lifetime of deteriorating structures. Journal of Performance of Constructed Facilities, 25(6), 534–544. doi:10.1061/(ASCE)CF.1943-5509.0000197
  • Kim, S., Ge, B., & Frangopol, D. M. (2019). Effective optimum maintenance planning with updating based on inspection information for fatigue-sensitive structures. Probabilistic Engineering Mechanics, 58, 103003, doi:10.1016/j.probengmech.2019.103003
  • Kim, S., Ge, B., & Frangopol, D. M. (2021). Optimum bridge life-cycle management with updating based on inspected fatigue crack under uncertainty. Proceedings of the Tenth International Conference on Bridge Maintenance, Safety, and Management (IABMAS2020), Sapporo, Japan, April 11–15, 2021; in Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations, H. Yokota and D.M. Frangopol, eds., CRC Press/Balkema, Taylor & Francis Group plc, London.
  • Kolios, A., Mytilinou, V., Lozano-Minguez, E., & Salonitis, K. (2016). A comparative study of multiple-criteria decision-making methods under stochastic inputs. Energies, 9(7), 566. doi:10.3390/en9070566
  • Kullback, S., & Leibler, R. A. (1951). On information and sufficiency. The Annals of Mathematical Statistics, 22(1), 79–86. doi:10.1214/aoms/1177729694
  • Li, Z., Zhang, Y., & Wang, C. (2013). A sensor-driven structural health prognosis procedure considering sensor performance degradation. Structure and Infrastructure Engineering, 9(8), 764–776. doi:10.1080/15732479.2011.614259
  • Liu, M., Frangopol, D. M., & Kim, S. (2009a). Bridge safety evaluation based on monitored live load effects. Journal of Bridge Engineering, 14(4), 257–269. doi:10.1061/(ASCE)1084-0702(2009)14:4(257)
  • Liu, M., Frangopol, D. M., & Kim, S. (2009b). Bridge system performance assessment from structural health monitoring: A case study. Journal of Structural Engineering, 135(6), 733–742. doi:10.1061/(ASCE)ST.1943-541X.0000014
  • Luque, J., & Straub, D. (2019). Risk-based optimal inspection strategies for structural systems using dynamic Bayesian networks. Structural Safety, 76, 68–80. doi:10.1016/j.strusafe.2018.08.002
  • Ma, Y., Zhang, J., Wang, L., & Liu, Y. (2013). Probabilistic prediction with Bayesian updating for strength degradation of RC bridge beams. Structural Safety, 44, 102–109. doi:10.1016/j.strusafe.2013.07.006
  • Macke, M., & Higuchi, S. (2007). Optimizing maintenance interventions for deteriorating structures using cost-benefit criteria. Journal of Structural Engineering, 133(7), 925–934. doi:10.1061/(ASCE)0733-9445(2007)133:7(925)
  • Madsen, H. O., Sørensen, J. D., & Olesen, R. (1990). Optimal inspection planning for fatigue damage of offshore structures. Proceedings of the 5th International Conference on Structural Safety and Reliability: Structural Safety and Reliability, San Francisco, US, pp. 2099–2106.
  • Madsen, H. O., Torhaug, R., & Cramer, E. H. (1991). Probability-based cost benefit analysis of fatigue design, inspection and maintenance. Proceedings of the Marine Structural Inspection, Maintenance and Monitoring Symposium, SSC/SNAME, Arlington, VA, II.E.1–12.
  • Marler, R. T., & Arora, J. S. (2010). The weighted sum method for multi-objective optimization: New insights. Structural and Multidisciplinary Optimization, 41(6), 853–862. doi:10.1007/s00158-009-0460-7
  • MathWorks. (2021). Optimization Toolbox™ user’s guide. MathWorks.
  • Moan, T. (2005). Reliability-based management of inspection, maintenance and repair of offshore structures. Structure and Infrastructure Engineering, 1(1), 33–62. doi:10.1080/15732470412331289314
  • Mohanty, P. P., Mahapatra, S. S., Mohanty, A., & Sthitapragyan. (2018). A novel multi-attribute decision making approach for selection of appropriate product conforming ergonomic considerations. Operations Research Perspectives, 5, 82–93. doi:10.1016/j.orp.2018.01.004
  • Mori, Y., & Ellingwood, B. R. (1994a). Maintaining reliability of concrete structures. I: Role of inspection/repair. Journal of Structural Engineering, 120(3), 824–845. doi:10.1061/(ASCE)0733-9445(1994)120:3(824)
  • Mori, Y., & Ellingwood, B. R. (1994b). Maintaining reliability of concrete structures. II: Optimum inspection/repair. Journal of Structural Engineering, 120(3), 846–862. doi:10.1061/(ASCE)0733-9445(1994)120:3(846)
  • NCHRP. (1979). Detection and repair of fatigue damage in welded highway bridges. NCHRP-report 206, Transportation Research Board, Washington, DC.
  • NCHRP. (2003). Bridge life-cycle cost analysis. NCHRP-report 483, Transportation Research Board, Washington, DC.
  • Neal, R. M. (2003). Slice sampling. Annals of Statistics, 31(3), 705–767.
  • Nijkamp, P., & Blaas, E. (1994). Impact assessment and evaluation in transportation planning. Kluwer Academic Publishers.
  • Okasha, N.M., & Frangopol, D.M. (2012). Integration of structural health monitoring in a system performance-based life-cycle bridge management framework. Structure and Infrastructure Engineering, 8(11), 999–1016. doi:10.1080/15732479.2010.485726
  • Onoufriou, T., & Frangopol, D. M. (2002). Reliability-based inspection optimization of complex structures: A brief retrospective. Computers & Structures, 80(12), 1133–1144. doi:10.1016/S0045-7949(02)00071-8
  • Orcesi, A.D., & Frangopol, D.M. (2011). Optimization of bridge maintenance strategies based on structural health monitoring information. Structural Safety, 33(1), 26–41. doi:10.1016/j.strusafe.2010.05.002
  • Paris, P., & Erdogan, F. (1963). A critical analysis of crack propagation laws. Journal of Basic Engineering, 85(4), 528–533. doi:10.1115/1.3656900
  • Rastogi, R., Ghosh, S., Ghosh, A. K., Vaze, K. K., & Singh, P. K. (2017). Fatigue crack growth prediction in nuclear piping using Markov chain Monte Carlo simulation. Fatigue & Fracture of Engineering Materials & Structures, 40(1), 145–156. doi:10.1111/ffe.12486
  • Saaty, T. L. (2003). Decision-making with the AHP: Why is the principal eigenvalue necessary. European Journal of Operational Research, 145(1), 85–91. doi:10.1016/S0377-2217(02)00227-8
  • Sabatino, S., & Frangopol, D. M. (2017). Decision making framework for optimal SHM planning of ship structures considering availability and utility. Ocean Engineering, 135, 194–206. doi:10.1016/j.oceaneng.2017.02.030
  • Shannon, C. E. (1948). The mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. doi:10.1002/j.1538-7305.1948.tb01338.x
  • Soliman, M., & Frangopol, D. M. (2014). Life-cycle management of fatigue sensitive structures integrating inspection information. Journal of Infrastructure Systems, 20(2), 04014001. doi:10.1061/(ASCE)IS.1943-555X.0000169
  • Soliman, M., Frangopol, D. M., & Kim, S. (2013). Probabilistic optimum inspection planning of steel bridges with multiple fatigue sensitive details. Engineering Structures, 49, 996–1006. doi:10.1016/j.engstruct.2012.12.044
  • Soliman, M., Frangopol, D. M., & Mondoro, A. (2016). A probabilistic approach for optimizing inspection, monitoring, and maintenance actions against fatigue of critical ship details. Structural Safety, 60, 91–101. doi:10.1016/j.strusafe.2015.12.004
  • Sony, S., Laventure, S., & Sadhu, A. (2019). A literature review of next-generation smart sensing technology in structural health monitoring. Structural Control and Health Monitoring, 26(3), e2321. doi:10.1002/stc.2321
  • Steyvers, M. (2011). Computational statistics with Matlab. Lecture, University of California Irvine.
  • Stillwell, W. G., Seaver, D. A., & Edwards, W. (1981). A comparison of weight approximation techniques in multiattribute utility decision making. Organizational Behavior and Human Performance, 28(1), 62–77. https://doi.org/10.1002/stc.2321 doi:10.1016/0030-5073(81)90015-5
  • Straub, D., & Faber, M. H. (2005). Risk based inspection planning for structural systems. Structural Safety, 27(4), 335–355. doi:10.1016/j.strusafe.2005.04.001
  • Suo, Q., & Stewart, M. G. (2009). Corrosion cracking prediction updating of deteriorating RC structures using inspection information. Reliability Engineering & System Safety, 94(8), 1340–1348. doi:10.1016/j.ress.2009.02.011
  • Tang, W. H., & Yen, B. C. (1991). Dam safety inspection scheduling. Journal of Hydraulic Engineering, 117(2), 214–229. doi:10.1061/(ASCE)0733-9429(1991)117:2(214)
  • Thanapol, Y., Akiyama, M., & Frangopol, D. M. (2016). Updating the seismic reliability of existing RC structures in a marine environment by incorporating the spatial steel corrosion distribution: Application to bridge piers. Journal of Bridge Engineering, 21(7), 04016031. doi:10.1061/(ASCE)BE.1943-5592.0000889
  • Thoft-Christensen, P., & Sørensen, J. D. (1987). Optimal strategy for inspection and repair of structural systems. Civil Engineering Systems, 4(2), 94–100. doi:10.1080/02630258708970464
  • Triantaphyllou, E. (2000). Multi-criteria decision making methods: A comparative study. Springer.
  • Voogd, H. (1983). Multicriteria evaluation for urban and regional planning. Pion.
  • Wang, Y. M., & Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling, 51(1–2), 1–12. doi:10.1016/j.mcm.2009.07.016
  • Willmott, C., & Matsuura, K. (2005). Advantages of the Mean Absolute Error (MAE) over the Root Mean Square Error (RMSE) in assessing average model performance. Climate Research, 30(1), 79–82. doi:10.3354/cr030079
  • Xiujuan, L., & Zhongke, S. (2004). Overview of multi-objective optimization methods. Journal of System Engineering and Electronics, 15(2), 142–146.
  • Xing, C., Caspeele, R., & Taerwe, L. (2016). Optimization of SHM and maintenance planning based on Bayesian joint modeling of time-dependent measurements and hazard functions. Proceedings of the Eighth International Conference on Bridge Maintenance, Safety and Management (IABMAS2016), Foz do Iguaçu, Brazil, June 26–30, 2016: in Maintenance, Monitoring, Safety, Risk and Resilience of Bridges and Bridge Networks, T.N. Bittencourt, D.M. Frangopol, and A.T. Beck, eds., CRC Press/Balkema, Taylor & Francis Group plc, London.
  • Xu, Y., & Brownjohn, J. M. W. (2018). Review of machine‐vision based methodologies for displacement measurement in civil structures. Journal of Civil Structural Health Monitoring, 8(1), 91–110. doi:10.1007/s13349-017-0261-4
  • Yeh, C. H. (2002). A problem-based selection of multi-attribute decision-making methods. International Transactions in Operational Research, 9(2), 169–181. doi:10.1111/1475-3995.00348
  • Yoon, K. P., & Hwang, C. L. (1995). Multiple attribute decision making: An introduction. SAGE Publication Inc.
  • Zhu, B., & Frangopol, D.M. (2013a). Risk-based approach for optimum maintenance of structures under traffic and earthquake loads. Journal of Structural Engineering, 139(3), 422–434. doi:10.1061/(ASCE)ST.1943-541X.0000671
  • Zhu, B., and Frangopol, D.M. (2013b). Reliability assessment of ship structures using Bayesian updating. Engineering Structures, 56, 1836–1847. doi:10.1016/j.engstruct.2013.07.024
  • Zhu, B., and Frangopol, D.M. (2013c). Incorporation of SHM data on load effects in the reliability and redundancy assessment of ships using Bayesian updating. Structural Health Monitoring, 12(4), 377–392. doi:10.1177/1475921713495082
  • Zou, G., Banisoleiman, K., & González, A. (2018). Probabilistic decision basis and objectives for inspection planning and optimization. Proceedings of the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE2018), Ghent, Belgium, October 28–31, 2018; in Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision, R. Caspelle, L. Taerwe, and D. M. Frangopol, eds., CRC Press/Balkema, Taylor & Francis Group plc, London.

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